def randomUniform(generatedFilename):
infileString, outfolderMC, outfolderRS, gpumcmlDirectory, gpumcmlExecutable = systemPaths.initPaths(
)
infile = open(infileString)
BVFs, Vss, ds, SaO2s, rs, nrSamples, photons, wavelengths, FWHM, eHbO2, eHb, nrSimulations = simulation.perfect(
)
reflectances = np.zeros((nrSimulations, len(wavelengths)))
parameters = np.zeros((nrSimulations, 4))
print('start simulations...')
#%% start program logic
start = time.time()
for i in range(nrSimulations):
print('starting simulation ' + str(i) + ' of ' + str(nrSimulations))
BVF = random.uniform(min(BVFs), max(BVFs))
Vs = random.uniform(min(Vss), max(Vss))
d = random.uniform(min(ds), max(ds))
r = random.uniform(min(rs), max(rs))
SaO2 = random.uniform(min(SaO2s), max(SaO2s))
parameters[i, :] = np.array([BVF, Vs, d, SaO2])
for j, wavelength in enumerate(wavelengths):
reflectanceValue = mch.runOneSimulation(wavelength,
eHbO2,
eHb,
infile,
outfolderMC,
gpumcmlDirectory,
gpumcmlExecutable,
BVF,
Vs,
d,
r,
SaO2,
Fwhm=FWHM,
nrPhotons=photons)
print((BVF, Vs, d, SaO2, r, wavelength))
# here, summarize result from wavelength in reflectance spectrum
reflectances[i, j] = reflectanceValue
infile.close()
# save the reflectance results!
now = datetime.datetime.now().strftime("%Y%B%d%I:%M%p")
np.save(
outfolderRS + now + generatedFilename + "reflectances" + str(photons) +
"photons", reflectances)
np.save(
outfolderRS + now + generatedFilename + str(nrSimulations) +
"parameters", parameters)
end = time.time()
print "total time to generate random uniform data: " + str((end - start))
def perfectGrid(generatedFilename):
infileString, outfolderMC, outfolderRS, gpumcmlDirectory, gpumcmlExecutable = systemPaths.initPaths(
)
infile = open(infileString)
BVFs, Vss, ds, SaO2s, rs, nrSamples, photons, wavelengths, FWHM, eHbO2, eHb, nrSimulations = simulation.perfect(
)
reflectances = np.zeros((nrSamples, len(wavelengths)))
print('start simulations...')
#%% start program logic
start = time.time()
currentSimulation = 0
params = itertools.product(BVFs, Vss, ds, SaO2s, rs)
paramsList = list(itertools.product(BVFs, Vss, ds, SaO2s, rs))
for BVF, Vs, d, SaO2, r in params:
print('starting simulation ' + str(currentSimulation) + ' of ' +
str(nrSamples))
for idx, wavelength in enumerate(wavelengths):
# here the magic happens: run monte carlo simulation for tissue parameters
# and specific wavelength
reflectanceValue = mch.runOneSimulation(wavelength,
eHbO2,
eHb,
infile,
outfolderMC,
gpumcmlDirectory,
gpumcmlExecutable,
BVF,
Vs,
d,
r,
SaO2,
Fwhm=FWHM,
nrPhotons=photons)
print((BVF, Vs, d, SaO2, r, wavelength))
# here, summarize result from wavelength in reflectance spectrum
reflectances[currentSimulation, idx] = reflectanceValue
currentSimulation += 1
infile.close()
# save the reflectance results!
now = datetime.datetime.now().strftime("%Y%B%d%I:%M%p")
np.save(
outfolderRS + now + generatedFilename + "reflectances" + str(photons) +
"photons", reflectances)
np.save(
outfolderRS + now + generatedFilename + str(nrSamples) + "parameters",
paramsList)
end = time.time()
print "total time for generating perfect data on grid: " + str(
(end - start))
def randomUniform(generatedFilename):
# the input file without the run specific parameters for ua, us and d:
infileString = 'data/colonTemplate.mci'
infile = open(infileString)
# the output folder for the mc simulations
outfolderMC = 'outputMC/'
# the output folder for the reflectance spectra
outfolderRS = 'outputRS/'
# the input file without the run specific parameters for ua, us and d:
infileString = 'data/colonTemplate.mci'
infile = open(infileString)
# the output folder for the mc simulations
# attention: this is relative to your gpumcml path!
outfolderMC = 'outputMC/'
# the output folder for the reflectance spectra
outfolderRS = 'data/output/'
gpumcmlDirectory = '/home/wirkert/workspace/monteCarlo/gpumcml/fast-gpumcml/'
gpumcmlExecutable = 'gpumcml.sm_20'
BVFs, Vss, ds, SaO2s, rs, nrSamples, photons, wavelengths, FWHM, eHbO2, eHb, nrSimulations = simulation.perfect(
)
reflectances = np.zeros((nrSimulations, len(wavelengths)))
parameters = np.zeros((nrSimulations, 5))
print('start simulations...')
#%% start program logic
start = time.time()
for i in range(nrSimulations):
print('starting simulation ' + str(i) + ' of ' + str(nrSimulations))
BVF = random.uniform(min(BVFs), max(BVFs))
Vs = random.uniform(min(Vss), max(Vss))
d = random.uniform(min(ds), max(ds))
r = random.uniform(min(rs), max(rs))
SaO2 = random.uniform(min(SaO2s), max(SaO2s))
parameters[i, :] = np.array([BVF, Vs, d, r, SaO2])
for j, wavelength in enumerate(wavelengths):
reflectanceValue = mch.runOneSimulation(wavelength,
eHbO2,
eHb,
infile,
outfolderMC,
gpumcmlDirectory,
gpumcmlExecutable,
BVF,
Vs,
d,
r,
SaO2,
Fwhm=FWHM,
nrPhotons=photons)
print((BVF, Vs, d, SaO2, r, wavelength))
# here, summarize result from wavelength in reflectance spectrum
reflectances[i, j] = reflectanceValue
infile.close()
# save the reflectance results!
now = datetime.datetime.now().strftime("%Y%B%d%I:%M%p")
np.save(
outfolderRS + now + generatedFilename + "reflectances" + str(photons) +
"photons", reflectances)
np.save(outfolderRS + now + generatedFilename + "parameters", parameters)
end = time.time()
print "total time to generate random uniform data: " + str((end - start))
def randomUniform(generatedFilename):
# the input file without the run specific parameters for ua, us and d:
infileString = 'data/colonTemplate.mci'
infile = open(infileString)
# the output folder for the mc simulations
outfolderMC = 'outputMC/'
# the output folder for the reflectance spectra
outfolderRS = 'outputRS/'
# the input file without the run specific parameters for ua, us and d:
infileString = 'data/colonTemplate.mci'
infile = open(infileString)
# the output folder for the mc simulations
# attention: this is relative to your gpumcml path!
outfolderMC ='outputMC/'
# the output folder for the reflectance spectra
outfolderRS = 'data/output/'
gpumcmlDirectory = '/home/wirkert/workspace/monteCarlo/gpumcml/fast-gpumcml/'
gpumcmlExecutable = 'gpumcml.sm_20'
BVFs, Vss, ds, SaO2s, rs, nrSamples, photons, wavelengths, FWHM, eHbO2, eHb, nrSimulations = simulation.perfect()
reflectances = np.zeros((nrSimulations, len(wavelengths)))
parameters = np.zeros((nrSimulations, 5))
print('start simulations...')
#%% start program logic
start = time.time()
for i in range(nrSimulations):
print('starting simulation ' + str(i) + ' of ' + str(nrSimulations))
BVF = random.uniform(min(BVFs), max(BVFs))
Vs = random.uniform(min(Vss), max(Vss))
d = random.uniform(min(ds), max(ds))
r = random.uniform(min(rs), max(rs))
SaO2= random.uniform(min(SaO2s), max(SaO2s))
parameters[i,:] = np.array([BVF, Vs, d, r, SaO2])
for j, wavelength in enumerate(wavelengths):
reflectanceValue = mch.runOneSimulation(
wavelength, eHbO2, eHb,
infile, outfolderMC, gpumcmlDirectory, gpumcmlExecutable,
BVF, Vs, d,
r, SaO2,
Fwhm = FWHM, nrPhotons=photons)
print((BVF, Vs, d, SaO2, r, wavelength))
# here, summarize result from wavelength in reflectance spectrum
reflectances[i, j] = reflectanceValue
infile.close()
# save the reflectance results!
now = datetime.datetime.now().strftime("%Y%B%d%I:%M%p")
np.save(outfolderRS + now + generatedFilename + "reflectances" + str(photons) + "photons", reflectances)
np.save(outfolderRS + now + generatedFilename + "parameters", parameters)
end = time.time()
print "total time to generate random uniform data: " + str((end - start))
def perfectGrid(generatedFilename):
# the input file without the run specific parameters for ua, us and d:
infileString = "data/colonTemplate.mci"
infile = open(infileString)
# the output folder for the mc simulations
# attention: this is relative to your gpumcml path!
outfolderMC = "outputMC/"
# the output folder for the reflectance spectra
outfolderRS = "data/output/"
gpumcmlDirectory = "/home/wirkert/workspace/monteCarlo/gpumcml/fast-gpumcml/"
gpumcmlExecutable = "gpumcml.sm_20"
BVFs, Vss, ds, SaO2s, rs, nrSamples, photons, wavelengths, FWHM, eHbO2, eHb = simulation.perfect()
reflectances = np.zeros((nrSamples, len(wavelengths)))
print ("start simulations...")
#%% start program logic
start = time.time()
currentSimulation = 0
params = itertools.product(BVFs, Vss, ds, SaO2s, rs)
paramsList = list(itertools.product(BVFs, Vss, ds, SaO2s, rs))
for BVF, Vs, d, SaO2, r in params:
print ("starting simulation " + str(currentSimulation) + " of " + str(nrSamples))
for idx, wavelength in enumerate(wavelengths):
# here the magic happens: run monte carlo simulation for tissue parameters
# and specific wavelength
reflectanceValue = mch.runOneSimulation(
wavelength,
eHbO2,
eHb,
infile,
outfolderMC,
gpumcmlDirectory,
gpumcmlExecutable,
BVF,
Vs,
d,
r,
SaO2,
Fwhm=FWHM,
nrPhotons=photons,
)
print ((BVF, Vs, d, SaO2, r, wavelength))
# here, summarize result from wavelength in reflectance spectrum
reflectances[currentSimulation, idx] = reflectanceValue
currentSimulation += 1
infile.close()
# save the reflectance results!
now = datetime.datetime.now().strftime("%Y%B%d%I:%M%p")
np.save(outfolderRS + now + generatedFilename + "reflectances" + str(photons) + "photons", reflectances)
np.save(outfolderRS + now + generatedFilename + "parameters", parameters)
end = time.time()
print "total time for generating perfect data on grid: " + str((end - start))
def perfectGrid(generatedFilename):
# the input file without the run specific parameters for ua, us and d:
infileString = 'data/colonTemplate.mci'
infile = open(infileString)
# the output folder for the mc simulations
# attention: this is relative to your gpumcml path!
outfolderMC = 'outputMC/'
# the output folder for the reflectance spectra
outfolderRS = 'data/output/'
gpumcmlDirectory = '/home/wirkert/workspace/monteCarlo/gpumcml/fast-gpumcml/'
gpumcmlExecutable = 'gpumcml.sm_20'
BVFs, Vss, ds, SaO2s, rs, nrSamples, photons, wavelengths, FWHM, eHbO2, eHb = simulation.perfect(
)
reflectances = np.zeros((nrSamples, len(wavelengths)))
print('start simulations...')
#%% start program logic
start = time.time()
currentSimulation = 0
params = itertools.product(BVFs, Vss, ds, SaO2s, rs)
paramsList = list(itertools.product(BVFs, Vss, ds, SaO2s, rs))
for BVF, Vs, d, SaO2, r in params:
print('starting simulation ' + str(currentSimulation) + ' of ' +
str(nrSamples))
for idx, wavelength in enumerate(wavelengths):
# here the magic happens: run monte carlo simulation for tissue parameters
# and specific wavelength
reflectanceValue = mch.runOneSimulation(wavelength,
eHbO2,
eHb,
infile,
outfolderMC,
gpumcmlDirectory,
gpumcmlExecutable,
BVF,
Vs,
d,
r,
SaO2,
Fwhm=FWHM,
nrPhotons=photons)
print((BVF, Vs, d, SaO2, r, wavelength))
# here, summarize result from wavelength in reflectance spectrum
reflectances[currentSimulation, idx] = reflectanceValue
currentSimulation += 1
infile.close()
# save the reflectance results!
now = datetime.datetime.now().strftime("%Y%B%d%I:%M%p")
np.save(
outfolderRS + now + generatedFilename + "reflectances" + str(photons) +
"photons", reflectances)
np.save(outfolderRS + now + generatedFilename + "parameters", parameters)
end = time.time()
print "total time for generating perfect data on grid: " + str(
(end - start))
def randomUniform(generatedFilename):
infileString, outfolderMC, outfolderRS, gpumcmlDirectory, gpumcmlExecutable = systemPaths.initPaths()
infile = open(infileString)
BVFs, Vss, ds, SaO2s, rs, nrSamples, photons, wavelengths, FWHM, eHbO2, eHb, nrSimulations = simulation.perfect()
reflectances = np.zeros((nrSimulations, len(wavelengths)))
parameters = np.zeros((nrSimulations, 4))
print('start simulations...')
#%% start program logic
start = time.time()
for i in range(nrSimulations):
print('starting simulation ' + str(i) + ' of ' + str(nrSimulations))
BVF = random.uniform(min(BVFs), max(BVFs))
Vs = random.uniform(min(Vss), max(Vss))
d = random.uniform(min(ds), max(ds))
r = random.uniform(min(rs), max(rs))
SaO2= random.uniform(min(SaO2s), max(SaO2s))
parameters[i,:] = np.array([BVF, Vs, d, SaO2])
for j, wavelength in enumerate(wavelengths):
reflectanceValue = mch.runOneSimulation(
wavelength, eHbO2, eHb,
infile, outfolderMC, gpumcmlDirectory, gpumcmlExecutable,
BVF, Vs, d,
r, SaO2,
Fwhm = FWHM, nrPhotons=photons)
print((BVF, Vs, d, SaO2, r, wavelength))
# here, summarize result from wavelength in reflectance spectrum
reflectances[i, j] = reflectanceValue
infile.close()
# save the reflectance results!
now = datetime.datetime.now().strftime("%Y%B%d%I:%M%p")
np.save(outfolderRS + now + generatedFilename + "reflectances" + str(photons) + "photons", reflectances)
np.save(outfolderRS + now + generatedFilename + str(nrSimulations) + "parameters", parameters)
end = time.time()
print "total time to generate random uniform data: " + str((end - start))
def perfectGrid(generatedFilename):
infileString, outfolderMC, outfolderRS, gpumcmlDirectory, gpumcmlExecutable = systemPaths.initPaths()
infile = open(infileString)
BVFs, Vss, ds, SaO2s, rs, nrSamples, photons, wavelengths, FWHM, eHbO2, eHb, nrSimulations = simulation.perfect()
reflectances = np.zeros((nrSamples, len(wavelengths)))
print ("start simulations...")
#%% start program logic
start = time.time()
currentSimulation = 0
params = itertools.product(BVFs, Vss, ds, SaO2s, rs)
paramsList = list(itertools.product(BVFs, Vss, ds, SaO2s, rs))
for BVF, Vs, d, SaO2, r in params:
print ("starting simulation " + str(currentSimulation) + " of " + str(nrSamples))
for idx, wavelength in enumerate(wavelengths):
# here the magic happens: run monte carlo simulation for tissue parameters
# and specific wavelength
reflectanceValue = mch.runOneSimulation(
wavelength,
eHbO2,
eHb,
infile,
outfolderMC,
gpumcmlDirectory,
gpumcmlExecutable,
BVF,
Vs,
d,
r,
SaO2,
Fwhm=FWHM,
nrPhotons=photons,
)
print ((BVF, Vs, d, SaO2, r, wavelength))
# here, summarize result from wavelength in reflectance spectrum
reflectances[currentSimulation, idx] = reflectanceValue
currentSimulation += 1
infile.close()
# save the reflectance results!
now = datetime.datetime.now().strftime("%Y%B%d%I:%M%p")
np.save(outfolderRS + now + generatedFilename + "reflectances" + str(photons) + "photons", reflectances)
np.save(outfolderRS + now + generatedFilename + str(nrSamples) + "parameters", paramsList)
end = time.time()
print "total time for generating perfect data on grid: " + str((end - start))